Autonomous Optical Navigation Schemes And Nonlinear Filter Algorithms Simulation Of Spacecraft

Because the communication delay introduced by the further distance of deep space for ground navigating methods is very large, autonomous navigation technology of spacecraft has become a key one in the deep-space exploring fields. And autonomous optical navigation is the most effective method in which all kinds of optical information from the sensors can be used in the autonomous navigation system. And the methods can also reduce the complexity of operation, reduce task costs and reduce the complexity of ground systems, which can significantly enhance the independent survivability and expand further potentiality on space applications of spacecraft; What is more, the design and application of filter algorithms is the key one in the autonomous optical navigation system.With supports of the National High Technology Research and Development Program of China (863 Program) 'Autonomous Navigation Technology of Deep Spacecraft', this dissertation analyses the domestic and foreign situations on autonomous optical navigation of spacecraft, and studies the applications of nonlinear filter algorithms for autonomous optical navigation in deep space. The main contents of this dissertation are as follows:Firstly, the basic issues of autonomous optical navigation technology and the current development on navigation of domestic and foreign for deep space are introduced, and plenty of valuable references about exploring small bodies are also further introduced in the dissertation. And then the dynamics orbit models of spacecraft are set up and the principles of autonomous optical navigation are also proposed to build well-grounded base for the further researching.Secondly, the different navigation schemes of autonomous optical navigation are studied and put into the different missions of deep space. Because of the different relative dynamics orbit equations, corresponding autonomous optical navigation methods are proposed in different flight phases. Meanwhile, the related parameters and errors in the process are also under the analysis. Because of nonlinear state functions of the system, the general Extended Kalman Filter (EKF) and High-rank EKF are proposed in the. autonomous optical navigation system and then their advantages and disadvantages are analyzed respectively. Because of the limit on the word-length, running speed and memory of the computer, one EKF method based on Upper-triangular and Diagonal decomposition (UD-EKF) on autonomous optical navigation is proposed to solve the problem and then its merits on speed is shown by comparison to EKF as well. Because of filtering diversity of general EKF caused by strong nonlinear transferring matrix in the system equations, the Unscented Kalman Filter(UKF) and Square-Root Unscented Kalman Filter(SR-UKF) are introduced to solve the above problems, especially in which it is not necessary to solve the Jacobian matrix, and they both can obtain the stable convergence. Further, one reduced sigma-points algorithm is proposed in the autonomous optical navigation system, which can promote the running speed of computer as well as the filtering precision.Finally, for traits of different navigation missions, the above filtering algorithms are compared on precision, running speed and convergence and then the advantages and disadvantages are also analyzed as well as their respective effects in different fields. From the simulation result, the effects of above algorithms are also shown respectively.